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Staff Data Engineer Jobs in Washington (NOW HIRING)

Staff Data Engineer

Arlington, VA · Remote

$185K - $220K/yr

We are seeking a Staff Data Engineer to join our growing Product Engineering team. In this role, your primary responsibility will be to design, build, and maintain data processing, storage, and ...

Xometry is looking for a Staff Data Engineer to join our Data Platform team. This is a senior individual contributor role with broad technical scope and high organizational impact. You will own data ...

Xometry is looking for a Staff Data Engineer to join our Data Platform team. This is a senior individual contributor role with broad technical scope and high organizational impact. You will own data ...

Staff Data Engineer

Arlington, VA · On-site +1

$145K - $175K/yr

The Forterra Data Team is seeking an experienced Staff Data Engineer to support the implementation and development of data pipelines, the data warehouse, and other key components of the data platform.

Staff Data Engineer

Arlington, VA · On-site

$145K - $175K/yr

The Forterra Data Team is seeking an experienced Staff Data Engineer to support the implementation and development of data pipelines, the data warehouse, and other key components of the data platform.

Staff Data Engineer - TS/SCI Cleared

Arlington, VA · On-site

$131K - $158K/yr

You'll partner closely with engineers and intelligence analysts to turn messy, high-volume operational data into reliable, well-modeled systems that drive real missions. You'll also lead technical ...

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Data Engineer

Washington, DC · Remote

$98K - $128K/yr

The Data Engineer / Data Project Lead oversees data-focused staff assigned to the contract, ensures high-quality, secure, and sustainable data solutions, and applies user-centered, iterative ...

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Data Engineer

Washington, DC · On-site

$129K - $155K/yr

This contract supports the Joint Staff Strategy, Plans, and Policy Directorate (J5), through its ... The Data Engineer supports the J5 data infrastructure underpinning all of these functions, building ...

Data Engineer

Mclean, VA · Hybrid

$115K - $139K/yr

As the Data Engineer, you will also contribute to a variety of areas including ... Work directly with internal resources as well as customer technology staff to implement and support ...

Data Engineer

Mclean, VA · Hybrid

$115K - $139K/yr

As the Data Engineer, you will also contribute to a variety of areas including ... Work directly with internal resources as well as customer technology staff to implement and support ...

Data Engineer

Mclean, VA · On-site

$115K - $139K/yr

As the Data Engineer, you will also contribute to a variety of areas including: • Work directly with internal resources as well as customer technology staff to implement and support custom TRSS ...

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Staff Data Engineer information

See Washington salary details

$26.1K

$112.5K

$218K

How much do staff data engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for staff data engineer in Washington is $112,501.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,100.00 and $141,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a staff data engineer, and why are they important?

To thrive as a Staff Data Engineer, you need advanced proficiency in data architecture, programming (such as Python, Java, or Scala), and experience with large-scale data systems, supported by a bachelor's or master's degree in computer science or a related field. Familiarity with big data tools (Hadoop, Spark), cloud platforms (AWS, GCP, or Azure), and relevant certifications like Google Professional Data Engineer or AWS Data Analytics are typically required. Strong problem-solving abilities, effective communication, and leadership skills help drive cross-functional projects and mentor junior engineers. These skills ensure the design, implementation, and maintenance of robust data infrastructure that supports organizational decision-making and scalability.

What is a staff data engineer?

Staff Data Engineers are senior-level professionals responsible for designing, building, and maintaining large-scale data processing systems and architectures. They often lead technical initiatives, set data engineering standards, and mentor other engineers within a company. Staff Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure reliable and efficient data pipelines. Their role requires deep expertise in data modeling, ETL processes, distributed systems, and cloud technologies. They play a crucial part in enabling organizations to make data-driven decisions at scale.

How does a staff data engineer typically collaborate with cross-functional teams to deliver data-driven solutions?

As a Staff Data Engineer, you’ll frequently partner with data scientists, analysts, and product managers to understand project requirements and design scalable data systems. You'll be responsible for translating business needs into technical specifications, recommending best practices, and mentoring junior engineers. Collaboration often involves participating in sprint planning, code reviews, and architecture discussions to ensure data solutions are robust, secure, and aligned with organizational goals. Effective communication and a proactive approach to problem-solving are key to successful collaboration in this role.

What is the difference between Staff Data Engineer vs Data Engineer?

AspectStaff Data EngineerData Engineer
Required CredentialsBachelor's or Master's in CS, experience with big data toolsBachelor's in CS or related field, some experience with data pipelines
Work EnvironmentSenior-level, cross-team collaboration, leadership rolesEntry to mid-level, focused on building data pipelines
Employer & Industry UsageTech companies, large enterprises, data-driven organizationsStartups, small to medium enterprises, tech firms

The main difference is that a Staff Data Engineer typically has more experience, leadership responsibilities, and works on complex projects across teams, whereas a Data Engineer focuses on developing and maintaining data pipelines at an operational level.

Infographic showing various Staff Data Engineer job openings in Washington as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $112,501 per year, or $54.1 per hour.

Staff Data Engineer

Shift5

Arlington, VA • Remote

$185K - $220K/yr

Full-time

Re-posted 5 days ago


Job description

About Shift5

Shift5 is building the data platform for onboard operational technology (OT). We deliver cybersecurity, predictive maintenance, and compliance capabilities that enable defense and commercial fleets to operate with greater readiness, resilience, and mission assurance.

We are seeking a Staff Data Engineer to join our growing Product Engineering team. In this role, your primary responsibility will be to design, build, and maintain data processing, storage, and integration pipelines while acting as a force-multiplier for your team. You will report to our Off Vehicle Manager, Software Engineering, and operate in a team-based environment with engineers, product managers, program managers, and designers to conceive, implement, and shape major features. You'll be a major factor in generating high-impact products that literally save lives.

What You'll Do
  • Design & Build Pipelines: Design, build, and maintain robust, scalable batch and streaming data processing, storage, and integration pipelines using technologies such as Apache Airflow or Benthos.
  • Feature Ownership & Leadership: Interpret requirements and design specifications, taking full ownership of building features from the ground up. Mentor and lead the rest of your team to deliver the right solutions.

  • Write Quality Code: Write clean, well-documented, scalable, extensible, and testable code to ensure application quality and maintainability.

  • Cross-Functional Collaboration: Partner with data scientists and engineers to create semantic data models representing complex vehicular systems, and integrate applications cleanly across other Shift5 componentry.

  • Support Stakeholders: Build scalable data products for data scientists, transportation engineers, and executives to drive insights and decision-making.

  • Cloud Optimization: Create efficient, reliable, cost-effective, dynamically scalable, and observable solutions utilizing AWS cloud services.

  • Data Analysis & Quality: Analyze complex data sets to create data ontologies, verify data quality/integrity, and ensure data accuracy throughout pipelines.

  • Field Support: Support the design process and occasionally travel to customer sites (estimated a few times per year) to collaborate with Field Engineers on data integration and deployment.

What Success Looks Like
  • High-Impact Delivery: You successfully deliver scalable, observable, supportable, and reliable data processing applications that empower customers to run smarter, safer fleets.
  • End-to-End Ownership: You confidently steer complex data applications from scratch—including requirements gathering, design, planning, and implementation—in a fast-paced environment.

  • Collaborative Impact: You actively shape product design alongside multidisciplinary teams, acting as a technical leader and force-multiplier for your peers.

  • Adaptability: You efficiently multitask and smoothly accommodate changing priorities on demand to meet the dynamic needs of a scaling company.

What We're Looking For

Required:

  • Engineering Experience: 6+ years of software/data engineering experience with a deep understanding of software engineering practices and concepts.

  • Core Languages: 6+ years of experience with a major programming language (GoLang, Java, or Python).

  • Databases & Big Data: 6+ years of relational database experience (PostgreSQL, MySQL, Oracle, etc.) alongside 6+ years of experience with Big Data (Hadoop, Spark) and Data Modeling.

  • Cloud & Containers: 4+ years of experience with containerization and cloud services (Docker, Kubernetes) and cloud monitoring tools.

  • Data Pipelines & Stack: Expertise with batch and streaming data pipelines (Apache Airflow, Benthos) and familiarity with modern data stack components (ingestion, transformation, orchestration).

Preferred:

  • U.S. citizenship required and ability to obtain a security clearance.
  • Education: MS in Computer Science, Cybersecurity, Cyber Intelligence, or equivalent.

  • Data Architecture: Experience and understanding of data lakes/warehouses (e.g., Snowflake, Databricks, Redshift).

  • DevOps Practices: Proficiency with CI/CD, source control, design reviews, and integrating observable practices.

  • Advanced Languages & Tools: Experience with Rust, SDK design, and implementation (including code gen of type-specific bindings to Python, Go, TypeScript).

  • Travel Flexibility: Willingness to travel occasionally to customer and partner sites to support field integration and deployment efforts.

Compensation & Benefits
  • Base Salary: $185,000 - $220,000

  • Bonus program and equity in a fast-growing startup

  • Competitive medical, dental, and vision coverage for employees and their families

  • Health Savings Account with annual employer contributions

  • Employer-paid Life and Disability Insurance

  • Uncapped paid time off policy 

  • Flexible work & remote work policy 

  • Tax-deferred public transit benefits with Metro SmartBenefits (DC/MD/VA) 

We are committed to building an inclusive culture of belonging that embraces the diversity of our people and represents the communities in which we work and the customers we serve. We know the happiest and highest performing teams include people with diverse perspectives and ways of solving problems. We strive to attract and retain talent from all backgrounds and create workplaces where everyone feels empowered to bring their full, authentic selves to work.  

Shift5 is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sexual orientation, gender identify, national origin, disability, age, marital status, ancestry, projected veteran status, or any other protected group or class. 

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